Evaluation of Microbiota Transplant Therapy in Patients With Alopecia Areata

Alopecia Areata (AA) is among the most highly prevalent human autoimmune diseases, leading to disfiguring hair loss due to the collapse of immune privilege of the hair follicle and subsequent autoimmune attack. AA affects about 5.3 million people in the United States alone, including males and females across all ethnic groups, with a lifetime risk of 2.1%. Autoimmunity develops against the hair follicle, resulting in non-scarring hair loss that may begin as patches that can coalesce and progress to cover the entire scalp (alopecia totalis) or eventually the entire body (alopecia universalis). In AA, there is no permanent destruction of the hair follicle, and regrowth remains possible. Treatment options for AA include intralesional steroids, topical anthralin, allergic contact dermatitis with diphencyprone (DPCP), dinitrochlorobenzene (DNCB), or squaric acid dibutyl ester (SADBE), and recently janus kinase ( JAK) inhibitors. Despite the recent approval of JAKs for the treatment of extensive alopecia areata, some patients are treatment resistant, suffer relapses, or cannot take an oral immunosuppressive medication.

This study will attempt to elucidate the pre-treatment and post treatment skin and gut microbiome composition to determine whether specific bacterial species may correlate with disease or treatment response. To determine the effects of MTT on immune cell composition and activation systemically and locally in the skin, we will analyze major immune cell populations in peripheral blood samples and collect skin biopsies for histopathology and next generation sequencing analyses. Further, to determine if changes in immune cell populations affect the inflammatory response, we will profile inflammatory cytokines. To identify if changes in the gut microbiota influence the metabolic signature in AA, we will also perform untargeted metabolomics in stool gut microbiome samples and in plasma. Altogether, this comprehensive approach aims to identify the pathogenic immunological mechanisms associated with microbiome composition correlated to pre-treatment disease, post-treatment response, and any non-responders to treatment.